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Digital Fraud Wiki

Your source for the latest fraud intelligence, insights, research, and commentary.

Common Payment Fraud Scams: How to Stay Safe

What is payment fraud

Payment fraud is any deceptive activity aiming to steal funds during a payment. In most cases, fraudsters can access a victim’s payment credentials without their knowledge.

What are common types of payment fraud

Credit and Debit Card Fraud

In credit card frauds, fraudsters use someone’s credit card without permission. They can steal the card outright or get the details needed through card skimming and other scams.

Debit card frauds work in the same way, but the fraudster needs more information, like the PIN. In either case, fraudsters can create cloned cards or buy leaked card information on the dark web.

Identity Theft

Fraudsters often target Social Security numbers and bank account credentials for theft. These details allow them to make fraudulent transactions, open new accounts, and make payments as someone else. Identity theft is one of the most common forms of payment fraud.

Phishing Scams

Fraudsters send deceptive emails or messages posing as legitimate organizations to trick individuals into revealing their sensitive financial information, such as passwords or credit card details. Once they have the information they can use it in for a range of payment frauds.

Wire fraud

Wire fraud is any financial fraud committed using electronic communications. It often includes other frauds like phishing or stolen identity. The legal scope of wire fraud goes beyond payments, but it’s still a common form of payment fraud.

Online Payment Fraud (Card Not Present Fraud)

This includes fraudulent activities conducted through online platforms or payment systems. It can involve fake online stores, fraudulent auctions, or unauthorized transactions on e-commerce websites. In cases where transactions happen online with stored card information, it results in card not present fraud.

Check Fraud

Fraudsters illegally create or alter checks to withdraw funds from an account or pay for goods and services. There are many check fraud tactics, including forgery, check kiting, paperhanging, and outright stealing.

Invoice Fraud

Fraudsters send fake invoices pretending to be legitimate businesses, tricking victims into payment. They may use real information or create seemingly real businesses that are actually fake. Once the invoice is paid, it goes to the fraudster who hides the source of the funds.

Push Payment Fraud

Push payment fraud, also known as authorized payment fraud, is a scam where the actual account holder makes the payment. Fraudsters trick them using social engineering tactics to convince the victim the payment is safe. They might pose as a bank employee, offer a job, or even seek romantic interest.

Push payment fraud is especially damaging in cases like Zelle Fraud, because the account holder is on the hook for the payment. Banks won’t take responsibility or cover the fraud losses because the account holder authorized the payment.

Mobile Payment Fraud

As mobile payment methods gained popularity, fraudsters learned to exploit their vulnerabilities. They can hijack users’ apps or exploit stolen credentials to carry out fraudulent transactions.

Account Takeover

Bad actors use stolen credentials to lock the true account holder out and take control. Once they have the account, they can make purchases, transfer money, or create fake checks.

Chargeback Fraud

This is a form of first-party fraud, meaning the actual account holder is the one committing the fraud. In chargeback frauds, buyers make a purchase then lie and claim they never got what they paid for. The card issuer refunds the money and the fraudster keeps both the item or service and their payment.

How to detect payment fraud

Financial institutions and merchants have a few systems they rely on to detect payment fraud. All require proactive measures, vigilant monitoring, and effective fraud detection tools.

Card and geolocation verification work together to verify who is actually making a payment. Geolocation compares the customer’s physical location or IP address with the transaction’s origin. Sudden changes, like transactions from distant locations in a short time, may signal potential fraud.

Card Verification Value (CVV) checks, address verification services (AVS), or 3D Secure authentication protocols help confirm the authenticity of payments and reduce fraud risk.

Likewise, transaction monitoring checks for patterns of suspicious activities. Then, anomalies in these patterns trigger alerts for further investigation. During these manual reviews, experienced fraud analysts investigate and can prevent fraud if they spot it.

How AI detects and prevents payment fraud

AI (Artificial Intelligence) has revolutionized how organizations detect and preventing payment fraud.

Device fingerprinting techniques identify unique characteristics of devices used in transactions. This helps detect if a device has been associated with previous fraudulent activities. AI’s behavior analysis analyzes vast amounts of historical data to spot patterns and detect anomalies.

AI-powered systems like DataVisor‘s monitor transactions in real-time. This enables the immediate identification and prevention of fraudulent transactions.

Machine learning models automatically learn and adapt to new fraud patterns. Unsupervised machine learning (UML) algorithms can detect unknown or emerging fraud patterns. That’s because it sees outliers in transaction data without relying on pre-defined fraud labels. This allows UML to uncover previously unseen fraud patterns and adapt to evolving fraud tactics.

Natural Language Processing (NLP) techniques can analyze customer messages, chat logs, or social media interactions to spot fraud-related content or phishing. This is a powerful tool in combatting social engineering

All of these capabilities are essential to not only detecting payment fraud, but staying ahead of new methods. To learn how DataVisor detects and prevents payment fraud with best-in-class response time, book a personalized demo.